IEEE VR Conference
IEEE VR Conference 27 March – 3 April | Virtual The IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR) is the premier international event for the presentation of research results in the broad areas of virtual, augmented, and mixed reality (VR/AR/XR). …
An Ethical Crisis in Computing?
Moshe Y. Vardi, RICE UNIVERSITY – Abstract: IST Distinguished Lecture Computer scientists think often of "Ender's Game" these days. In this award-winning 1985 science-fiction novel by Orson Scott Card, Ender is being trained at Battle School, an institution designed to make young children into military…
POSTPONED – Ethics of, and Trust in, Artificial Intelligence
Mariarosaria Taddeo, University of Oxford – Abstract: I will analyse the ethical opportunities and risks that artificial intelligence (AI) brings about and how ethical analyses can help to harness the potential for good of AI and mitigate its risks. Bio Dr Mariarosaria Taddeo is Research…
CANCELED – Introduction to Compact Data Structures: A Strategy for Big Data Processing
Nieves Brisaboa, Universidad de la Coruña – Abstract: The need to deal with huge amounts of data (big data world) has motivated the development of new data structures able to represent data and indexes to access them in compact space. The key idea in this…
Introduction to IOTA — a feeless cryptocurrency
, IOTA Foundation – Abstract: In this talk we discuss the basics of the IOTA cryptosystem: its main principles and approach to the consensus (a.k.a. Coordicide). Bio Serguei Popov is a research mathematician working in the field of Probability Theory and Stochastic Processes. He graduated…
Talks on Model Driven Engineering & Artificial Intelligence Approaches
António Menezes Leitão João Penha-Lopes , – Abstract: 3rd Talk/2020: IST, 24/January/2020, with Prof. António Menezes Leitão (IST) and Dr. João Penha-Lopes (Quidgest) The department of Computer Science and Engineering from Instituto Superior Técnico and Quidgest associates to promote a series of meetings with guest…
Focusing the Macroscope: How We Can Use Data to Understand Behavior
Joana Gonçalves de Sá, Universidade Nova de Lisboa – Abstract: Individual decisions can have a large impact on society as a whole. This is obvious for political decisions, but still true for small, daily decisions made by common citizens. Individuals decide how to vote, whether…
Hardware Engineering in ARM
Francisco Gaspar, ARM – Abstract: In this talk, Francisco Gaspar will explain what a Hardware Engineer at ARM can accomplish in his role, and try to transmit both the importance and the expectations from the Design, Verification and Implementation sides of it. He will start…
Cloud computing overview and Running code on Google Cloud
Wesley Chun, Google – Abstract: Cloud computing has taken over industry by storm, yet there aren’t enough new college grads who know enough about it. This session begins with a vendor-agnostic, high-level overview of cloud computing, including its three primary service levels. This is followed…
Scaling Distributed Machine Learning with In-Network Aggregation
Marco Canini, KAUST: King Abdullah University of Science and Technology – Abstract: Training complex machine learning models in parallel is an increasingly important workload. We accelerate distributed parallel training by designing a communication primitive that uses a programmable switch dataplane to execute a key step…
11th Lisbon Machine Learning Summer School
LxMLS 2021 will take place July 7th to July 15th in online format (via zoom and slack). It is organized jointly by Instituto Superior Técnico (IST), a leading Engineering and Science school in Portugal, the Instituto de Telecomunicações, the Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID), Unbabel and Cleverly.
Click here for information about past editions (LxMLS 2011, LxMLS 2012, LxMLS 2013, LxMLS 2014, LxMLS 2015, LxMLS 2016, LxMLS 2017, LxMLS 2018, LxMLS 2019, LxMLS 2020) and to watch the videos of the lectures (2016, 2017, 2018, 2020).
Call for Participation
* Application Deadline: May 15, 2021
* Decision: June 1, 2021
* Early Registration: June 15 – July 1, 2021
* Summer School: July 7 – 15, 2021
Topics and Intended Audience
The school will cover a range of Machine Learning (ML) topics, from theory to practice, that are important in solving Natural Language Processing (NLP) problems that arise in the analysis and use of Web data.
Our target audience is:
- Researchers and graduate students in the fields of NLP and Computational Linguistics;
- Computer scientists who have interests in statistics and machine learning;
- Industry practitioners who desire a more in depth understanding of these subjects.
Features of LxMLS:
- No deep previous knowledge of ML or NLP is required, but the attendants are assumed to have some basic background on mathematics and programming
- Lecturers are leading researchers in machine learning and natural language processing (see speakers)
- Days are divided into morning lectures and afternoon lab sessions and practical talks (see schedule)
- The Labs guide will be provided one month in advance. Last year’s guide can be found here
- A day zero is scheduled to review basic concepts and introduce the necessary tools for implementation exercises
- Both basic (e.g linear classifiers) and advanced topics (e.g. deep learning, reinforcement learning) will be covered
Due to the current COVID-19 pandemic, the 11th Lisbon Machine Learning School will be held online (via zoom and slack). Similar to last year, we are excited for the opportunity to create a virtual school, where you will be able to attend all the lectures, and participate in the Q&As and labs remotely. We will also provide the tools for students to engage with each other remotely. The lectures will also be streamed to YouTube, and will become freely available later in our YouTube channel. The Q&A, labs and social activities will remain restricted to the accepted students only.
List of Confirmed Speakers
LUIS PEDRO COELHO Fudan University | China
MÁRIO FIGUEIREDO Instituto de Telecomunicações & Instituto Superior Técnico | Portugal
ANDRE MARTINS Instituto de Telecomunicações & Unbabel | Portugal
IRYNA GULEYVICH Technical University Darmstat | Germany
NOAH SMITH University of Washington & Allen Institute for Artificial Intelligence | USA
SLAV PETROV Google Inc. | USA
XAVIER CARRERAS dMetrics | USA
GRAHAM NEUBIG Carnegie Mellon University | USA
BHIKSHA RAJ Carnegie Mellon University | USA
CHRIS DYER Google Deep Mind | UK
ELIAS BARENBOIM Columbia University | USA
ADELE RIBEIRO Columbia University | USA
STEFAN RIEZLER Institut für Computerlinguistik, Universität Heidelberg | Germany
BARBARA PLANK IT University of Copenhagen | Denmark
SASHA RUSH Cornell Tech | USA
Please visit the webpage for up to date information: http://lxmls.it.pt/2021
To apply, please fill the form in https://lisbonmls.wufoo.com/forms/application-form-lxmls-2021/
Any questions should be directed to: email@example.com.
International European Conference on Parallel and Distributed Computing
The 27th International European Conference on Parallel and Distributed Computing (Euro-Par 2021) will take from August 30 to September 3 2021 in Lisbon.
Euro-Par is the prime European conference covering all aspects of parallel and distributed processing, ranging from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to full-fledged applications, from architecture, compiler, language and interface design and implementation, to tools, support infrastructures, and application performance aspects.
The 2021 edition of Euro-Par will be organized as a collaboration between INESC-ID and Instituto Superior Técnico (IST).
– Abstract Submission: February 5, 2021
– Paper Submission Deadline: February 12, 2021
– Author Notification: April 30, 2021
– Camera-Ready Papers: June 6, 2021
More information is available here.